source: https://hifld-geoplatform.opendata.arcgis.com/datasets/mobile-home-parks
Using data from the US Department of Homeland Security, I have plotted locations of trailer parks across New York State. It appears most trailer parks have fewer than 50 trailers and are unsurprisingly concentrated Upstate.
# Marker Point Map
# Load mobile home data
pal <- colorFactor(c("mediumturquoise", "purple" , "cadetblue4" ), domain = c("LARGE (>100)", "MEDIUM (51-100)","SMALL (<50)"))
basemap_points <-leaflet(mobile_home_ny) %>%
# Basemaps
addTiles()%>%
addProviderTiles("Esri.WorldPhysical", group = "WorldPhysical") %>%
addCircleMarkers(group = mobile_home_ny$SIZE, stroke = F, color = ~pal(SIZE), weight = 50,
fillOpacity = 0.5) %>%
addLayersControl(
baseGroups = c("OSM (default)", "WorldPhysical"),
overlayGroups = c(levels(mobile_home_ny$SIZE)),
options = layersControlOptions(collapsed = FALSE))%>%
addLegend("bottomright", pal = pal, values = ~SIZE,
title = "Size of Mobile Home Community")## Assuming "LONGITUDE" and "LATITUDE" are longitude and latitude, respectivelybasemap_points %>%
fitBounds(-78, 45, -72, 40) # Fit to NYThis plot shows the public transit systems and the system authority under which the transit system runs under. Again, most of these transit systems are concentrated in New York City, with a very small transit line in Buffalo.
# LINE PLOT
# Load Shape File
public_transit <- readOGR("Public_Transit_Routes.shp")## OGR data source with driver: ESRI Shapefile
## Source: "G:\My Drive\Fall 2019\Mini 1\RShiny for Operations Management\HW\HW_2\HW2_nmurray\Public_Transit_Routes.shp", layer: "Public_Transit_Routes"
## with 316 features
## It has 17 fields
## Integer64 fields read as strings: OBJECTID ID UACODE# Limit to NY Transit Systems
ny_lines <- c("METRO-NORTH COMMUTER RAILROAD COMPANY, DBA: MTA METRO-NORTH RAILROAD",
"MTA LONG ISLAND RAIL ROAD",
"MTA NEW YORK CITY TRANSIT",
"NIAGARA FRONTIER TRANSPORTATION AUTHORITY",
"PORT AUTHORITY OF NEW YORK AND NEW JERSEY",
"PORT AUTHORITY TRANS-HUDSON CORPORATION",
"STATEN ISLAND RAPID TRANSIT OPERATING AUTHORITY, DBA: MTA STATEN ISLAND RAILWAY")
public_transit_ne <- subset(public_transit, public_transit$SYS_AGENCY %in% ny_lines)
#Create Color Pallette
cols <- colorRampPalette(brewer.pal(8,"Dark2"))(length(ny_lines))
pal2 <-colorFactor(cols, domain = ny_lines)
leaflet(data = public_transit_ne) %>%
# Basemaps
addTiles() %>%
addProviderTiles("Esri.WorldGrayCanvas", group = "WorldGrayCanvas") %>%
addProviderTiles("Esri.WorldTerrain", group = "WorldTerrain") %>%
addPolylines(group = public_transit_ne$SYS_AGENCY, color = ~pal2(SYS_AGENCY)) %>%
# Layers control
addLayersControl(
baseGroups = c("WorldGrayCanvas", "WorldTerrain"),
# overlayGroups = ne_lines,
# position = "bottomleft",
options = layersControlOptions(collapsed = FALSE)) %>%
addLegend("topright", pal = pal2, values = ~SYS_AGENCY,
title = " New York Public Transit Lines By System") %>%
fitBounds(-79, 48, -72, 39) # Fit to Northeast
Given that we know there are more mobiles homes Upstate and more transit lines downstate, one might infer that Downstate is where the population center is.
If Downstate has more transit lines, do they use fewer cars or does the difference in population outweight this? Based on this map, we conclude that Downstate has a much larger population and the different of population means more cares, irrespective of public transit.
Data source: https://www.census.gov/data.html
# Source: https://walkerke.github.io/tidycensus/reference/load_variables.html
# Get the data from the census
v17 <- load_variables(2017, "acs5", cache = TRUE)
# Vehicle Ownership
ny_data_car <- get_acs(geography = "county",
variables = c("B08541_006"),
state = 36,
geometry = FALSE)## Getting data from the 2012-2016 5-year ACS# Population
ny_data_pop <- get_acs(geography = "county",
variables = c("B01003_001"),
state = 36,
geometry = FALSE)## Getting data from the 2012-2016 5-year ACS# Get NYS county shapefile
ny_counties <- counties(state = 36)
# Merge Car and Population data files in a single file
poly_map_data <- merge(ny_data_car, ny_data_pop, by = c("GEOID", "NAME"), sort = FALSE)
ny_counties@data<- merge(ny_counties@data, poly_map_data, by = c("GEOID"), sort = FALSE)
#Merge Car and Shapefile data
cars_ny <- merge(ny_counties, ny_data_car, by = c("GEOID"))
# Recall Varible x is car data and variable.y is population data # Palette for Number of Cars
pal_car <- colorNumeric(
palette = "Reds",
na.color = "#808080",
domain = ny_counties$estimate.x) # of Cars
# Palette for Population
pal_ppl <- colorNumeric(
palette = "Purples",
na.color = "#808080",
domain = ny_counties$estimate.y) # population
basemap_poly <- leaflet(ny_counties) %>%
addTiles() %>%
addProviderTiles("Esri.WorldGrayCanvas", group = "WorldGrayCanvas") %>%
addProviderTiles("CartoDB.Positron", group = "Positron") %>%
fitBounds(-79, 45, -72, 39) # Fit to Northeast
basemap_poly %>%
addPolygons(
color = ~pal_car(estimate.x),
stroke = FALSE,
weight = 2,
opacity = 1,
dashArray = "3",
fillOpacity = 0.7,
group = "Number of Cars") %>%
addLegend(group = "Number of Cars", "bottomright",
pal = pal_car, values = ny_counties$estimate.x,
data = getMapData(basemap_poly),title = "Number of Cars") %>%
addPolygons(
color = ~pal_ppl(estimate.y),
stroke = FALSE,
weight = 2,
opacity = 1,
dashArray = "3",
fillOpacity = 1,
group = "Number of People")%>%
addLegend(group = "Number of People", "bottomright",
pal = pal_ppl, values = ny_counties$estimate.y,
data = getMapData(basemap_poly), title = "Number of People") %>%
addLayersControl(
baseGroups = c("WorldGrayCanvas", "Positron"),
overlayGroups = c("Number of Cars", "Number of People"),
options = layersControlOptions(collapsed = FALSE)) %>%
hideGroup("Number of People")